Performing data analysis is one of the core applications of dynamic scripting.  The combination of dynamic scripting and computational analysis libraries allows users to rapidly prototype and implement data analysis solutions.  To illustrate this, I recently downloaded a trial of NMath, a collection of software components from Centerspace Software that provides “numerical components for mathematical, financial, engineering, and scientific applications on the .NET platform,” and created a sample Inference in Word document that illustrates using these libraries.  The specific sample I created is based on CenterSpace’s own DataFrameExample, which demonstrates how to load sample data into a vector-based data storage object (called a “data frame”) and perform some simple data manipulations and statistical calculations.

 

When I re-created this example in Inference, I opted to store the data in an Inference in Excel DataFrame Document (complete with explicit data-typing), which I embedded in Inference in Word:

 

 

Then, I embedded the NMath assemblies into the Inference in Word document:

 

 

Next, I was able to add code blocks (comprising the data manipulation and statistical calculation code) and explanatory text to form a literate document:

 

 

When exported to a Microsoft Word Results Document, the data from the Excel DataFrame is loaded, and the code is executed against that DataFrame.  The resulting Word document combines the code and text of the original document with the code output to form a Results Document.  The screenshot below shows the permuted DataFrame columns:

 

 

This screenshot illustrates the generation of a column dictionary and calculation of some basic statistics:

 

 

This sample illustrates the ease with which data analysis can be performed and documented in Microsoft Office using Inference and available data analysis libraries, such as CenterSpace’s NMath.